Read e-book online A Unified Framework for Video Summarization, Browsing and PDF

By Ziyou Xiong, Regunathan Radhakrishnan, Ajay Divakaran, Yong Rui, Thomas S. Huang

ISBN-10: 012369387X

ISBN-13: 9780123693877

Huge volumes of video content material can in basic terms be simply accessed by means of fast searching and retrieval ideas. developing a video desk of contents (ToC) and video highlights to allow finish clients to sift via all this knowledge and locate what they need, once they wish are crucial. This reference places forth a unified framework to combine those services helping effective shopping and retrieval of video content material. The authors have built a cohesive option to create a video desk of contents, video highlights, and video indices that serve to streamline using functions in patron and surveillance video purposes.

The authors speak about the new release of desk of contents, extraction of highlights, diversified thoughts for audio and video marker popularity, and indexing with low-level good points comparable to colour, texture, and form. present functions together with this summarization and perusing expertise also are reviewed. functions similar to occasion detection in elevator surveillance, spotlight extraction from activities video, and photo and video database administration are thought of in the proposed framework. This booklet offers the newest in learn and readers will locate their look for wisdom comfortable via the breadth of the data coated during this quantity.

* deals the newest in innovative study and functions in surveillance and buyer video

* Presentation of a singular unified framework aimed toward effectively sifting throughout the abundance of pictures collected day-by-day at procuring department shops, airports, and different advertisement facilities

* Concisely written by means of top individuals within the sign processing with step by step guide in development video ToC and indices

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Additional info for A Unified Framework for Video Summarization, Browsing and Retrieval. With Applications to Consumer and Surveillance Video

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3 TIME-ADAPTIVE GROUPING Before we construct the scene structure, it is convenient to first create an intermediate entity group to facilitate the process. The purpose is to place similar shots into groups, since similar shots have a high possibility of being in the same scene. For shots to be similar, the following properties should be satisfied: • Visual similarity. Similar shots should be visually similar. That is, they should have similar spatial {Hist{bi) and Hist{ei)) and temporal {Acti) features.

For example, the batter can be on the right or left side of the catcher, or the umpire might be occluded by the catcher to different degrees. Robust identification of those video frames containing the catcher can bring us to the vicinity of the highlights. This motivates us to develop robust baseball catcher detection algorithms. 3. 2 The Two Soccer Goalposts We make use of the following two observations from soccer videos: • When most of the interesting plays such as goals, comer kicks, or penalty kicks take place, the goalpost is almost always in view.

65 and sceneThreshold = 0 gives good scene structure. 5. Note that sceneThreshold = 0 gives good scene structure. 5. These two probabilities indicate the following: • Only if a shot is very similar to a group (better than 74% of all the shots) can it be merged to the group. 4. 5 Experimental Results In all of the experiments reported in this section, the video streams are MPEG compressed, with the digitization rate equal to 30 frames per second. To validate the effectiveness of the proposed approach, representatives of various movie types are tested.

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A Unified Framework for Video Summarization, Browsing and Retrieval. With Applications to Consumer and Surveillance Video by Ziyou Xiong, Regunathan Radhakrishnan, Ajay Divakaran, Yong Rui, Thomas S. Huang


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